Michael Gormley

1.5k total citations
47 papers, 919 citations indexed

About

Michael Gormley is a scholar working on Pulmonary and Respiratory Medicine, Cancer Research and Molecular Biology. According to data from OpenAlex, Michael Gormley has authored 47 papers receiving a total of 919 indexed citations (citations by other indexed papers that have themselves been cited), including 31 papers in Pulmonary and Respiratory Medicine, 25 papers in Cancer Research and 15 papers in Molecular Biology. Recurrent topics in Michael Gormley's work include Prostate Cancer Treatment and Research (29 papers), Radiopharmaceutical Chemistry and Applications (15 papers) and Cancer, Lipids, and Metabolism (12 papers). Michael Gormley is often cited by papers focused on Prostate Cancer Treatment and Research (29 papers), Radiopharmaceutical Chemistry and Applications (15 papers) and Cancer, Lipids, and Metabolism (12 papers). Michael Gormley collaborates with scholars based in United States, United Kingdom and Germany. Michael Gormley's co-authors include Adam Ertel, Paolo Fortina, Guillermo M. Alexander, Ruby Gao, Rehman Qureshi, Seena K. Ajit, Ahmet Saçan, Yuzhen Tian, Marguerite K. McDonald and Richard G. Pestell and has published in prestigious journals such as Nature Communications, Journal of Clinical Oncology and Cancer Research.

In The Last Decade

Michael Gormley

44 papers receiving 911 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Michael Gormley United States 17 541 380 302 166 84 47 919
Lien Spans Belgium 16 489 0.9× 215 0.6× 400 1.3× 125 0.8× 60 0.7× 29 967
Rosario Gil‐Benso Spain 19 330 0.6× 176 0.5× 204 0.7× 146 0.9× 52 0.6× 45 867
Karin Jennbacken Sweden 20 469 0.9× 173 0.5× 256 0.8× 248 1.5× 98 1.2× 33 816
Ye Tian China 18 382 0.7× 246 0.6× 229 0.8× 191 1.2× 61 0.7× 79 867
Andreas Doll Spain 20 714 1.3× 344 0.9× 314 1.0× 296 1.8× 90 1.1× 37 1.3k
Qingjian Ou China 16 575 1.1× 306 0.8× 169 0.6× 258 1.6× 120 1.4× 81 1.1k
Jiang Zhu China 21 692 1.3× 515 1.4× 168 0.6× 177 1.1× 75 0.9× 75 1.2k
Kai Yin China 20 546 1.0× 411 1.1× 155 0.5× 230 1.4× 183 2.2× 54 1.1k
Xiaojun Zhou China 19 779 1.4× 611 1.6× 219 0.7× 190 1.1× 70 0.8× 85 1.2k
Qian Wei China 16 597 1.1× 425 1.1× 162 0.5× 166 1.0× 130 1.5× 33 871

Countries citing papers authored by Michael Gormley

Since Specialization
Citations

This map shows the geographic impact of Michael Gormley's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Michael Gormley with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Michael Gormley more than expected).

Fields of papers citing papers by Michael Gormley

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Michael Gormley. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Michael Gormley. The network helps show where Michael Gormley may publish in the future.

Co-authorship network of co-authors of Michael Gormley

This figure shows the co-authorship network connecting the top 25 collaborators of Michael Gormley. A scholar is included among the top collaborators of Michael Gormley based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Michael Gormley. Michael Gormley is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
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Sicotte, Hugues, Krishna R. Kalari, Sisi Qin, et al.. (2022). Molecular Profile Changes in Patients with Castrate-Resistant Prostate Cancer Pre- and Post-Abiraterone/Prednisone Treatment. Molecular Cancer Research. 20(12). 1739–1750. 9 indexed citations
3.
Cecil, Denise L., Ekram Gad, Michael Gormley, et al.. (2022). Anti-tumor activity of a T-helper 1 multiantigen vaccine in a murine model of prostate cancer. Scientific Reports. 12(1). 13618–13618. 3 indexed citations
4.
Smith, Matthew R., Shibu Thomas, Michael Gormley, et al.. (2021). Blood Biomarker Landscape in Patients with High-risk Nonmetastatic Castration-Resistant Prostate Cancer Treated with Apalutamide and Androgen-Deprivation Therapy as They Progress to Metastatic Disease. Clinical Cancer Research. 27(16). 4539–4548. 9 indexed citations
5.
Feng, Felix Y., Shibu Thomas, Fred Saad, et al.. (2021). Association of Molecular Subtypes With Differential Outcome to Apalutamide Treatment in Nonmetastatic Castration-Resistant Prostate Cancer. JAMA Oncology. 7(7). 1005–1005. 21 indexed citations
6.
Jayaram, Anuradha, Anna Wingate, Daniel Wetterskog, et al.. (2021). Plasma tumor gene conversions after one cycle abiraterone acetate for metastatic castration-resistant prostate cancer: a biomarker analysis of a multicenter international trial. Annals of Oncology. 32(6). 726–735. 36 indexed citations
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Belic, Jelena, Ricarda Graf, Thomas Bauernhofer, et al.. (2018). Genomic alterations in plasma DNA from patients with metastasized prostate cancer receiving abiraterone or enzalutamide. International Journal of Cancer. 143(5). 1236–1248. 40 indexed citations
10.
Wang, Guangxue, Michael Gormley, Jing Qiao, et al.. (2018). Cyclin D1-mediated microRNA expression signature predicts breast cancer outcome. Theranostics. 8(8). 2251–2263. 26 indexed citations
11.
Lam, Hung‐Ming, Ryan P. McMullin, Holly M. Nguyen, et al.. (2016). Characterization of an Abiraterone Ultraresponsive Phenotype in Castration-Resistant Prostate Cancer Patient-Derived Xenografts. Clinical Cancer Research. 23(9). 2301–2312. 17 indexed citations
12.
Babayan, Anna, Malik Alawi, Michael Gormley, et al.. (2016). Comparative study of whole genome amplification and next generation sequencing performance of single cancer cells. Oncotarget. 8(34). 56066–56080. 56 indexed citations
13.
Casimiro, Mathew C., Gabriele Di Sante, Xiaoming Ju, et al.. (2015). Cyclin D1 Promotes Androgen-Dependent DNA Damage Repair in Prostate Cancer Cells. Cancer Research. 76(2). 329–338. 32 indexed citations
14.
McDonald, Marguerite K., Yuzhen Tian, Rehman Qureshi, et al.. (2014). Functional significance of macrophage-derived exosomes in inflammation and pain. Pain. 155(8). 1527–1539. 272 indexed citations
15.
Casimiro, Mathew C., Michael Gormley, Hui Meng, et al.. (2013). Identification of a Cyclin D1 Network in Prostate Cancer That Antagonizes Epithelial–Mesenchymal Restraint. Cancer Research. 74(2). 508–519. 35 indexed citations
16.
Chen, Ke, Kongming Wu, Shaoxin Cai, et al.. (2013). Dachshund Binds p53 to Block the Growth of Lung Adenocarcinoma Cells. Cancer Research. 73(11). 3262–3274. 49 indexed citations
17.
Yu, Zuoren, Liping Wang, Chenguang Wang, et al.. (2013). Cyclin D1 induction of Dicer governs microRNA processing and expression in breast cancer. Nature Communications. 4(1). 2812–2812. 53 indexed citations
18.
Chen, Ke, Kongming Wu, Michael Gormley, et al.. (2013). Acetylation of the Cell-Fate Factor Dachshund Determines p53 Binding and Signaling Modules in Breast Cancer. Oncotarget. 4(6). 923–935. 21 indexed citations
19.
Meng, Rong, Michael Gormley, Vadiraja B. Bhat, Anne Rosenberg, & Andrew A. Quong. (2011). Low abundance protein enrichment for discovery of candidate plasma protein biomarkers for early detection of breast cancer. Journal of Proteomics. 75(2). 366–374. 34 indexed citations
20.
Gormley, Michael & Aydın Tözeren. (2008). Expression profiles of switch-like genes accurately classify tissue and infectious disease phenotypes in model-based classification. BMC Bioinformatics. 9(1). 486–486. 10 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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